{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "Transfer Learning for Computer Vision Tutorial\n",
    "==============================================\n",
    "**Author**: `Sasank Chilamkurthy <https://chsasank.github.io>`_\n",
    "\n",
    "In this tutorial, you will learn how to train a convolutional neural network for\n",
    "image classification using transfer learning. You can read more about the transfer\n",
    "learning at `cs231n notes <https://cs231n.github.io/transfer-learning/>`__\n",
    "\n",
    "Quoting these notes,\n",
    "\n",
    "    In practice, very few people train an entire Convolutional Network\n",
    "    from scratch (with random initialization), because it is relatively\n",
    "    rare to have a dataset of sufficient size. Instead, it is common to\n",
    "    pretrain a ConvNet on a very large dataset (e.g. ImageNet, which\n",
    "    contains 1.2 million images with 1000 categories), and then use the\n",
    "    ConvNet either as an initialization or a fixed feature extractor for\n",
    "    the task of interest.\n",
    "\n",
    "These two major transfer learning scenarios look as follows:\n",
    "\n",
    "-  **Finetuning the convnet**: Instead of random initializaion, we\n",
    "   initialize the network with a pretrained network, like the one that is\n",
    "   trained on imagenet 1000 dataset. Rest of the training looks as\n",
    "   usual.\n",
    "-  **ConvNet as fixed feature extractor**: Here, we will freeze the weights\n",
    "   for all of the network except that of the final fully connected\n",
    "   layer. This last fully connected layer is replaced with a new one\n",
    "   with random weights and only this layer is trained.\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# License: BSD\n",
    "# Author: Sasank Chilamkurthy\n",
    "\n",
    "from __future__ import print_function, division\n",
    "\n",
    "import torch\n",
    "import torch.nn as nn\n",
    "import torch.optim as optim\n",
    "from torch.optim import lr_scheduler\n",
    "import numpy as np\n",
    "import torchvision\n",
    "from torchvision import datasets, models, transforms\n",
    "import matplotlib.pyplot as plt\n",
    "import time\n",
    "import os\n",
    "import copy\n",
    "\n",
    "plt.ion()   # interactive mode"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Load Data\n",
    "---------\n",
    "\n",
    "We will use torchvision and torch.utils.data packages for loading the\n",
    "data.\n",
    "\n",
    "The problem we're going to solve today is to train a model to classify\n",
    "**ants** and **bees**. We have about 120 training images each for ants and bees.\n",
    "There are 75 validation images for each class. Usually, this is a very\n",
    "small dataset to generalize upon, if trained from scratch. Since we\n",
    "are using transfer learning, we should be able to generalize reasonably\n",
    "well.\n",
    "\n",
    "This dataset is a very small subset of imagenet.\n",
    "\n",
    ".. Note ::\n",
    "   Download the data from\n",
    "   `here <https://download.pytorch.org/tutorial/hymenoptera_data.zip>`_\n",
    "   and extract it to the current directory.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Data augmentation and normalization for training\n",
    "# Just normalization for validation\n",
    "data_transforms = {\n",
    "    'train': transforms.Compose([\n",
    "        transforms.RandomResizedCrop(224),\n",
    "        transforms.RandomHorizontalFlip(),\n",
    "        transforms.ToTensor(),\n",
    "        transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])\n",
    "    ]),\n",
    "    'val': transforms.Compose([\n",
    "        transforms.Resize(256),\n",
    "        transforms.CenterCrop(224),\n",
    "        transforms.ToTensor(),\n",
    "        transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])\n",
    "    ]),\n",
    "}\n",
    "\n",
    "data_dir = 'data/hymenoptera_data'\n",
    "image_datasets = {x: datasets.ImageFolder(os.path.join(data_dir, x),\n",
    "                                          data_transforms[x])\n",
    "                  for x in ['train', 'val']}\n",
    "dataloaders = {x: torch.utils.data.DataLoader(image_datasets[x], batch_size=4,\n",
    "                                             shuffle=True, num_workers=4)\n",
    "              for x in ['train', 'val']}\n",
    "dataset_sizes = {x: len(image_datasets[x]) for x in ['train', 'val']}\n",
    "class_names = image_datasets['train'].classes\n",
    "\n",
    "device = torch.device(\"cuda:0\" if torch.cuda.is_available() else \"cpu\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Visualize a few images\n",
    "^^^^^^^^^^^^^^^^^^^^^^\n",
    "Let's visualize a few training images so as to understand the data\n",
    "augmentations.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def imshow(inp, title=None):\n",
    "    \"\"\"Imshow for Tensor.\"\"\"\n",
    "    inp = inp.numpy().transpose((1, 2, 0))\n",
    "    mean = np.array([0.485, 0.456, 0.406])\n",
    "    std = np.array([0.229, 0.224, 0.225])\n",
    "    inp = std * inp + mean\n",
    "    inp = np.clip(inp, 0, 1)\n",
    "    plt.imshow(inp)\n",
    "    if title is not None:\n",
    "        plt.title(title)\n",
    "    plt.pause(0.001)  # pause a bit so that plots are updated\n",
    "\n",
    "\n",
    "# Get a batch of training data\n",
    "inputs, classes = next(iter(dataloaders['train']))\n",
    "\n",
    "# Make a grid from batch\n",
    "out = torchvision.utils.make_grid(inputs)\n",
    "\n",
    "imshow(out, title=[class_names[x] for x in classes])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Training the model\n",
    "------------------\n",
    "\n",
    "Now, let's write a general function to train a model. Here, we will\n",
    "illustrate:\n",
    "\n",
    "-  Scheduling the learning rate\n",
    "-  Saving the best model\n",
    "\n",
    "In the following, parameter ``scheduler`` is an LR scheduler object from\n",
    "``torch.optim.lr_scheduler``.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "def train_model(model, criterion, optimizer, scheduler, num_epochs=25):\n",
    "    since = time.time()\n",
    "\n",
    "    best_model_wts = copy.deepcopy(model.state_dict())\n",
    "    best_acc = 0.0\n",
    "\n",
    "    for epoch in range(num_epochs):\n",
    "        print('Epoch {}/{}'.format(epoch, num_epochs - 1))\n",
    "        print('-' * 10)\n",
    "\n",
    "        # Each epoch has a training and validation phase\n",
    "        for phase in ['train', 'val']:\n",
    "            if phase == 'train':\n",
    "                model.train()  # Set model to training mode\n",
    "            else:\n",
    "                model.eval()   # Set model to evaluate mode\n",
    "\n",
    "            running_loss = 0.0\n",
    "            running_corrects = 0\n",
    "\n",
    "            # Iterate over data.\n",
    "            for inputs, labels in dataloaders[phase]:\n",
    "                inputs = inputs.to(device)\n",
    "                labels = labels.to(device)\n",
    "\n",
    "                # zero the parameter gradients\n",
    "                optimizer.zero_grad()\n",
    "\n",
    "                # forward\n",
    "                # track history if only in train\n",
    "                with torch.set_grad_enabled(phase == 'train'):\n",
    "                    outputs = model(inputs)\n",
    "                    _, preds = torch.max(outputs, 1)\n",
    "                    loss = criterion(outputs, labels)\n",
    "\n",
    "                    # backward + optimize only if in training phase\n",
    "                    if phase == 'train':\n",
    "                        loss.backward()\n",
    "                        optimizer.step()\n",
    "\n",
    "                # statistics\n",
    "                running_loss += loss.item() * inputs.size(0)\n",
    "                running_corrects += torch.sum(preds == labels.data)\n",
    "            if phase == 'train':\n",
    "                scheduler.step()\n",
    "\n",
    "            epoch_loss = running_loss / dataset_sizes[phase]\n",
    "            epoch_acc = running_corrects.double() / dataset_sizes[phase]\n",
    "\n",
    "            print('{} Loss: {:.4f} Acc: {:.4f}'.format(\n",
    "                phase, epoch_loss, epoch_acc))\n",
    "\n",
    "            # deep copy the model\n",
    "            if phase == 'val' and epoch_acc > best_acc:\n",
    "                best_acc = epoch_acc\n",
    "                best_model_wts = copy.deepcopy(model.state_dict())\n",
    "\n",
    "        print()\n",
    "\n",
    "    time_elapsed = time.time() - since\n",
    "    print('Training complete in {:.0f}m {:.0f}s'.format(\n",
    "        time_elapsed // 60, time_elapsed % 60))\n",
    "    print('Best val Acc: {:4f}'.format(best_acc))\n",
    "\n",
    "    # load best model weights\n",
    "    model.load_state_dict(best_model_wts)\n",
    "    return model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Visualizing the model predictions\n",
    "^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
    "\n",
    "Generic function to display predictions for a few images\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "def visualize_model(model, num_images=6):\n",
    "    was_training = model.training\n",
    "    model.eval()\n",
    "    images_so_far = 0\n",
    "    fig = plt.figure()\n",
    "\n",
    "    with torch.no_grad():\n",
    "        for i, (inputs, labels) in enumerate(dataloaders['val']):\n",
    "            inputs = inputs.to(device)\n",
    "            labels = labels.to(device)\n",
    "\n",
    "            outputs = model(inputs)\n",
    "            _, preds = torch.max(outputs, 1)\n",
    "\n",
    "            for j in range(inputs.size()[0]):\n",
    "                images_so_far += 1\n",
    "                ax = plt.subplot(num_images//2, 2, images_so_far)\n",
    "                ax.axis('off')\n",
    "                ax.set_title('predicted: {}'.format(class_names[preds[j]]))\n",
    "                imshow(inputs.cpu().data[j])\n",
    "\n",
    "                if images_so_far == num_images:\n",
    "                    model.train(mode=was_training)\n",
    "                    return\n",
    "        model.train(mode=was_training)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finetuning the convnet\n",
    "----------------------\n",
    "\n",
    "Load a pretrained model and reset final fully connected layer.\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "model_ft = models.resnet18(pretrained=True)\n",
    "num_ftrs = model_ft.fc.in_features\n",
    "# Here the size of each output sample is set to 2.\n",
    "# Alternatively, it can be generalized to nn.Linear(num_ftrs, len(class_names)).\n",
    "model_ft.fc = nn.Linear(num_ftrs, 2)\n",
    "\n",
    "model_ft = model_ft.to(device)\n",
    "\n",
    "criterion = nn.CrossEntropyLoss()\n",
    "\n",
    "# Observe that all parameters are being optimized\n",
    "optimizer_ft = optim.SGD(model_ft.parameters(), lr=0.001, momentum=0.9)\n",
    "\n",
    "# Decay LR by a factor of 0.1 every 7 epochs\n",
    "exp_lr_scheduler = lr_scheduler.StepLR(optimizer_ft, step_size=7, gamma=0.1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Train and evaluate\n",
    "^^^^^^^^^^^^^^^^^^\n",
    "\n",
    "It should take around 15-25 min on CPU. On GPU though, it takes less than a\n",
    "minute.\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 0/24\n",
      "----------\n",
      "train Loss: 0.5480 Acc: 0.6639\n",
      "val Loss: 0.3938 Acc: 0.8431\n",
      "\n",
      "Epoch 1/24\n",
      "----------\n",
      "train Loss: 0.4366 Acc: 0.8279\n",
      "val Loss: 0.1971 Acc: 0.9281\n",
      "\n",
      "Epoch 2/24\n",
      "----------\n",
      "train Loss: 0.5933 Acc: 0.7623\n",
      "val Loss: 0.2538 Acc: 0.8824\n",
      "\n",
      "Epoch 3/24\n",
      "----------\n",
      "train Loss: 0.3787 Acc: 0.8566\n",
      "val Loss: 0.3070 Acc: 0.8824\n",
      "\n",
      "Epoch 4/24\n",
      "----------\n",
      "train Loss: 0.4787 Acc: 0.8443\n",
      "val Loss: 1.0034 Acc: 0.7386\n",
      "\n",
      "Epoch 5/24\n",
      "----------\n",
      "train Loss: 0.4688 Acc: 0.8074\n",
      "val Loss: 0.2524 Acc: 0.9020\n",
      "\n",
      "Epoch 6/24\n",
      "----------\n",
      "train Loss: 0.4411 Acc: 0.7951\n",
      "val Loss: 0.2519 Acc: 0.8889\n",
      "\n",
      "Epoch 7/24\n",
      "----------\n",
      "train Loss: 0.3792 Acc: 0.8566\n",
      "val Loss: 0.1802 Acc: 0.9281\n",
      "\n",
      "Epoch 8/24\n",
      "----------\n",
      "train Loss: 0.3381 Acc: 0.8811\n",
      "val Loss: 0.1564 Acc: 0.9477\n",
      "\n",
      "Epoch 9/24\n",
      "----------\n",
      "train Loss: 0.3781 Acc: 0.8197\n",
      "val Loss: 0.1718 Acc: 0.9346\n",
      "\n",
      "Epoch 10/24\n",
      "----------\n",
      "train Loss: 0.2735 Acc: 0.8770\n",
      "val Loss: 0.1720 Acc: 0.9346\n",
      "\n",
      "Epoch 11/24\n",
      "----------\n",
      "train Loss: 0.3575 Acc: 0.8525\n",
      "val Loss: 0.1592 Acc: 0.9412\n",
      "\n",
      "Epoch 12/24\n",
      "----------\n",
      "train Loss: 0.3415 Acc: 0.8484\n",
      "val Loss: 0.1809 Acc: 0.9346\n",
      "\n",
      "Epoch 13/24\n",
      "----------\n",
      "train Loss: 0.3078 Acc: 0.8566\n",
      "val Loss: 0.1826 Acc: 0.9346\n",
      "\n",
      "Epoch 14/24\n",
      "----------\n",
      "train Loss: 0.2316 Acc: 0.9057\n",
      "val Loss: 0.1787 Acc: 0.9346\n",
      "\n",
      "Epoch 15/24\n",
      "----------\n",
      "train Loss: 0.2631 Acc: 0.8975\n",
      "val Loss: 0.1754 Acc: 0.9346\n",
      "\n",
      "Epoch 16/24\n",
      "----------\n",
      "train Loss: 0.2950 Acc: 0.8730\n",
      "val Loss: 0.2314 Acc: 0.9216\n",
      "\n",
      "Epoch 17/24\n",
      "----------\n",
      "train Loss: 0.3041 Acc: 0.8770\n",
      "val Loss: 0.2147 Acc: 0.9216\n",
      "\n",
      "Epoch 18/24\n",
      "----------\n",
      "train Loss: 0.1791 Acc: 0.9303\n",
      "val Loss: 0.1803 Acc: 0.9281\n",
      "\n",
      "Epoch 19/24\n",
      "----------\n",
      "train Loss: 0.2684 Acc: 0.8934\n",
      "val Loss: 0.2181 Acc: 0.9346\n",
      "\n",
      "Epoch 20/24\n",
      "----------\n",
      "train Loss: 0.2042 Acc: 0.9057\n",
      "val Loss: 0.1762 Acc: 0.9346\n",
      "\n",
      "Epoch 21/24\n",
      "----------\n",
      "train Loss: 0.3441 Acc: 0.8443\n",
      "val Loss: 0.1763 Acc: 0.9216\n",
      "\n",
      "Epoch 22/24\n",
      "----------\n",
      "train Loss: 0.2227 Acc: 0.8934\n",
      "val Loss: 0.1801 Acc: 0.9412\n",
      "\n",
      "Epoch 23/24\n",
      "----------\n",
      "train Loss: 0.2752 Acc: 0.8770\n",
      "val Loss: 0.1926 Acc: 0.9281\n",
      "\n",
      "Epoch 24/24\n",
      "----------\n",
      "train Loss: 0.2250 Acc: 0.8770\n",
      "val Loss: 0.1848 Acc: 0.9412\n",
      "\n",
      "Training complete in 72m 38s\n",
      "Best val Acc: 0.947712\n"
     ]
    }
   ],
   "source": [
    "model_ft = train_model(model_ft, criterion, optimizer_ft, exp_lr_scheduler,\n",
    "                       num_epochs=25)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAGkAAABeCAYAAAAg/TovAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjAsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+17YcXAAAgAElEQVR4nO29a6wkSXbf9zsRkZn1us++fW+/e6a7Z3ZnhvvgPmlwlyuLlExR9gcJBgRbsk0ZtizAgGxBMAj7iw1btmnAgPzBgA0YtiQIoCUDoglRsrgUvYsFySWX5j45O7Pz7unpd/ft+6hbVZkZEef4Q9SsmsvZ5VDsS6qBPsDFrarMioyMk3HixP/8zykxM57Iv9zi/rg78ER+f3mipMdAnijpMZAnSnoM5ImSHgN5oqTHQP7YlSQif0dE/uby9WdF5JU/ouuaiFz5o7jWH1b+2JX0sJjZr5rZB36/80Tkp0Xk1/4o+vSHlYcfwn9ReaRKEpHwKNt7Iksxsx/4B1wF/nPgJWAP+NvAYHnsTwDXgZ8BbgN/b/n5vw58A9gHvgx8+KH2fhj4GjAF/gHw94G/+XB7D517Hvh54B6wC/zPwHNAC2TgCNhfntsA/yNwDbgD/K/A8KG2/jPgFnAT+PcBA678fve//O5fBl5e9vlN4D966Ni7Y/A3gLvLa/zl5bG/AkSgX/b1F5ef/wxwY9neK8CP/8Drv08lvbgcsE3g179nUBPwPywHaQh8bNnZTwMe+PeWbTRADbwN/HWgAv7N5U38HiUtv/tN4G8BY2AAfGZ57KeBX/uefv5PwD9a9nEF+EXgv18e+8ml4n5o2dbPPawk4N8GvvUDxuDPApcBAT4HzIGPfc8Y/NfLe/qp5fGN5fG/8+79Ld9/AHgHOLN8/xRw+VEo6a8+9P6ngDce6mDPcmYtP/tfgP/me9p4ZXlzP0Z5kuWhY1/+Pkr6VygzKLxHn36XkpaDN3v4Zpfff2v5+v8AfvahY8/yB5hJ73H9XwD+k4f6vHi4n5SH9Ee+j5KuLI//BFC9n+u93zXpnYdevw2ceej9PTNrH3p/EfgbIrL/7h9lFp5Z/t2wZW8fau+95Dzwtpml99G/k8AI+OpD1/yl5ecsr/u99/C+RUT+jIj8pog8WLb9U8DWQ6fsfk8/58Dkvdoys9eB/xT4r4C7IvL3ReTMe537rrxfJZ1/6PUFymz47nW/59x3gP/WzNYf+huZ2f9JsddnRUS+p733kneAC9/HGfnea96nPM0vPHTNNTN7d6Buvcc9vC8RkQb4h5T1bsfM1oH/hzJ734/8njCDmf2cmX2G8kAbZbn4vvJ+lfQfi8g5EdkE/gvKgv/95H8D/qqIfFqKjEXkz4rICvAbFPv910QkiMifBz71fdr5Lcrg/uyyjYGI/Ojy2B3gnIjUAGamy+v+LRHZBhCRsyLyry3P/7+AnxaR50VkBPyX7/O+oayjDcX0JhH5M8Cf/gN8/w5w6d03IvIBEfmTS+W3lIcr/6AG3q+Sfg74ZYpn8ybwff1+M/tt4D+keGJ7wOuUNQQz64E/v3y/B/wFivf2Xu1k4N+g2PBrFA/qLywPfwH4NnBbRO4vP/uZ5bV+U0QOgV+hLNKY2T+lOBZfWJ7zhYevJSJ/UUS+/X36MQX+GkXRexQn4x99v/t/D/nfgeeXZvgXKAr/Wcrsvw1sUx787yvyu5eH9zhB5CrwH5jZr/wBOvZEHqH8S4U4PJH3lidKegzk9zV3T+SPX57MpMdAnijpMZBjQa2/9Lf/O0vRwJb7PVEAvK/AwAWHYCiG+ApTxePoNeHNSNpjGTADETKGFwcGapBSRIJggIhQiaeuK/ygYRA8zjkqCUAG58uXnCfnjC7Ne4o9ZkYfIzn1xC4SNdP3C0DIMeF9wDmHOAfqyiMtQuU9g/EKSZU+gQ8OU4cqGMJP/ZW//n43uu9LjkVJMTmwiJmhLqFJCMEh2XDOY6Z47zHLOHzZu0tPRViqrkJICB5Vw2eQAMF7kpbBywreOaoQEOcI9QDnHF6E4D34ANlAIHkjENFgNNUYzYoPmRgF1Yz4EU0DOj/ER09OGdWMaSbUAfBU3qHqAAfBk5ynGa5iix7TFhdqiJFqOHzk43ksSsra4QxMDVXFiyfFhLkKsYwhmCUEQQ1EHKa5KEuFWgSVmmyZ4IUsRlUFUId3hogg3gg+lNnmHS5kKh8IVYXUA6rhCot+jsYeh0OqMU1VMV7dJDthOBiRxKG5xWJHO1tQV567t65y++pbODq81Th1+KqibhzB1Sw6YfvseY4WHZPxGuubDX3q6XWOb8Y0g41HPp7HoqTgK3JKJCBQgwPvHU4zLnhy7IkGLjR4a3HOYeZxvgGXAcM7cNSIF5xlRJZWUwJmRvCeygSqCnGO8WANP6iZnH6aycY2ZoI5ZTqfIh7GoxVms9sEP6ab32GBMO/vIN7RpymnzzzL4fSAM88/z6kLz3D7xjW8loenGdQc7O5y+YMfoncT6sGIU16Y7t8HMppneFaZrG8wHu88+vF85C0CRgJniCkOJarhqcgYqoY4Txc76gT4ITkrUhmiCVm6Mg6POfA4xDtMFbwDzYh3OBHUe0ZVgx9POPXCjxL8gFA7utThNOLqIROvxHjA7Ogqb939Tbw/gzCjcmOu336dsyeeYm//OjduvU7XH3HyxGkqVjlx9izBT7AoaM5sXHyWMFhlZW2Vvo/EvsevjJnN9sjOsTZZp+1nhO7gkY/nsSjJCagTUGORFHEeZz0KkJTgAg0VZq6sS95jyUiS0ajUlScHwWXDVWXmIJS1R4xkjtW1k8jKhJ2LH8YNGggtRk8KNd57FrNdUnvIrbtvoNl45+Y36eIRly+d4fXXrjNb3Cd4z8jvcDTrmM9ngMf7GX13k7sHr7Fz4ilWh5cZrY6ZrK2R1QjB4ahZLB7Q1GOms12mB3cZD9e5cfsNjBe5ePkjj3Q8j0VJqoZZBrXiGZHJXpCoOOdJJngPpoCUJxURvCk+OJSlI1XXxTlTRazCxBitnmSydY61C8/g6+L59SkxDqtMj+6CW3A02+XmvZfYP9plZ+M5ujhj3rWkXomLQGMb+Npz694rjEY3ePv6Kzx74QX2793n2vw2g2pEdSSA0K9GJvEkbTpibXySB/uJ8XCMZkN1Su2F2eKIa1e/ztWbL0E9f+TjeTzEEXVlAQmQU8Sbg+TAGWCQEjnUhACWMobhfCCZYX2PVBV1EoyM1gPEO6rBGuvbl9i58jw9CxKR3oTKO+LikG+//c9YXd/k9WtfZ3WwxVdf/iUcI+7dPeTW7bcQWXp688je4U2yb+liR3d9j8qvczTb5druG4xWAt4PaOoT3Ls3pRrscX9/ypkTidT1rKzucNAece3ai7TdEX3u+c6rX2NYG4ojzqePfDiPRUlV7bGYUDNcdphzoD1ZhJwE7wI5d8VzcjWC4MQVd9g5ggjRMk3OVLJOaIacfeYjsNIwy3v03ZR6MmZUn2T64C3eeec7zOIe9669zq07bxPXWtQcR4s75NwwGq9jGTbWVrl572UOuuskipu9EbaZxxlZjoiyy8EcjtpDxoMVBs0mt+4JI7/Og8M7XL3xEmurWwyrVe4+uM706D7ePJVTuv6Iuhoz0tEjH89jcsEV7yss9mRH2XeIW25uFcsJVYfznmyRUIWyyfRG7QNQYRijE9ucuPACzfqENPC08YCT4ysMB2Nu3vk2b0y/iLDO3uIGV65c4ef/8RdZGa3x1rWrpCyM69McTQ/JtkDEcX/3DQhzBn4TF4y2a/HiiZaZp7tI3TJpThFTx0Lv0bcz6BMH6T7zuE1D4No738RcRWUD2naBE2VlsIbXExAVUvPIx/OYeHIZzR4QPAbek1IClrt3y3gXUFEw6GPGe0+OiRyEjZObbJ1/mpNnLiOjmuliFzfr2Fjb4XB6g2l7j9sP3mTihuzPDvj6t77It176pwS/geYhziUe7F3F+YRQk1NmWJ9gZbLCUZdRFcZ+QD0cMW2PWB9tY7lloUfELoFzxE7BZRbMmQyGHD64gUVDXKapxuBqtlY2YQ6VNmjv6NqWmPSRj+bxuODqUIs4EXANqU+I57swkYSqoA66RCdcBjMMz87WeU7/0I+wsrPJrDuknx4wGDRQr9KsDvjWN3+FyUpm0e7x2vXrrE7OcGrnMvsP9tk7uMFkRTk6aOlbx8n1c8zaGX03JbZTGqlxgyGqSj8XxAkbg220jyRXZnrx3sYMR+s4HE4FLOLxDIcjTgxPUduYnDMsjK6LLPoORUgpIfpIESHg2JQEvVEwM1WUSE4ACe88GcgiSBByTnggO8/OuWe5/PHPIQPYPbyBrxoWXcuJkxd48bVf4rSd5Bu/83k+8tHPMN0PpJy59+AqV6+9zNrkFDka928fsrW2hWlL7R314BTBzRk2W+S+ZZ471lbGoIp3htKRXU+oBKcNldT0UTG3YFCNcFXF0K1ycnKa2iqqNACFPkLsIy4bIQS0N7CK7ncRpx6NHM+ahOEU1JScMykpakLhCClOwBt0CHioBxt84FM/xvqpS/hx4tqNV1G/YMNfZvOE46h9ja31i7z04jf55Md+kutv77O/9w4nT17m9jtXmTQrtP0eG6tb9NMj9qe3yXnOaP0sd/f2GExOsz+7RRNGrNYTBtWEuOhwvsV7pZKG3u2hRI6yJ/jAaDRhNTSs+/OMbJWwgLqq6JOimgnBkTOoCS5D1ALQyjEM6bEoSURQVVLKqBXzFzURREiqoI5aPJZ6QrPJM899mu1zl+h8z9Ubr5D1iItnP0I/97x15wtMxp533rzN/nTGb33jm1w4d4mnzj/Lyy/+DtP2GjdvXmOyvsrqaJt5OyOSGQ7GXNt9m8EoEPWIepCoQwZrmfYHhEFCQg9eCc6R2gOiKKPqJJOwxqRaZ63aYmu4Q5pmTBIxZiQLPgT6mBHnqR1EA19nPEK76B/5eB6Pkihutw8CKWEOavFkKxi3E2OREms723zyR/8cKyc3Oer32d19hxQj5858BO2NB4fXOLh/hxe/+TYH8328VQzqwNkzP8Q3v/J57s5ukfI+9XpNcAMaV0HTMnSQ6PDDHqqatp1xYvI0UTvC6AhPi0nCSyDnmthnHBM26oZmVDNxI87WH6SOQ6x1OF+2CKjDfJk14hKoEJwnaVcAZIOYF498PI8n6Cdlt54BFYc6hxpghlMjx8zOhWe4cPmTrGysMe0esHvwDtPDQy5d/Cj1QLDqiJR3USpOnfoALo0ZDVc4tXWBX//yzzPr7lE1Sp9apu016iqze3gbVzuSm7G6sspoOETdAdVYaOUWVZVQbRGnhOAwlBhnaM40UjGoVthwZ9kePE2Vh0h2SFYEAQJmkN8lqloFCDgQhCygllEeE+8ODG8ONcNEEPGYNzQbZo7xZJWLlz7M6pkd9rrb3Dm4zUp9krPnd5jNDyHscuvG27z61te59NQLfOtbv8nhwQ32pxnLgVm7y+bmSfr9KdJkJoMJFgJ9f59qaATAqj1EhUpGiAvUVUbdAaI1QiRnBfVghjhlsjJiq77ITnWZysYgDupl4NIyZkZKCsmhKeFdUdYiablHjNT3OOcf+Wgej5LEoS4Dgu+NhCv4mziSU05dfIHtp84ybW8zjwf0ixlrm88hznMwf5PX3vwS9/dfYnvnBW7evMtrb/8OOfc4EcaTVSzOkZRoOSA4R86O4A2qCnJfgNtYE9nHOU/fRULw1DIgkkkxM6gGTNt9hmFME0acqM9zsr7IOK+BZHqfqanpUyz3ZAaiRGJB+FXwzuMtYwI5FXTfcnzkw3ks5i5qJpvinCAuIBbJpqgGPvKJP8WVj36Mvf4adw9fp++Fi+c/werGhKzXmE73uHzh46S4wurwFF/52v/N6soAkYw4o+3uM58/4EBv4XyNl8CwnpDsiGhTghtiKH3OWLGxeFchKaCxIScD8+TOc3J8kY3ROS5MPszF8SdYYRMAoaZ2DYjDuVDMtzPAI+YQPCkrKSrZIMaE94KZkONjMpMEVxCEnMEHghmVCTKo2LlwCYZCPMzAkOFgk9rX3Lz7O3TtVWbzxGtv3Oad66/z2lv/H1E7HOsMB6v0fc+o2cC0whYBoaOqPClFYmoRn1AX6bopoaroouK7iqoaEDHMIsE3eBKjumIQBmz6i+wML1LFujDwxWNSwvyoUQl0QEoOU6OSmi4tCnrvgSx4V4MlcurIx+A4HM8+yRRQKh9QD9kptV/jcz/552jWTnL76GW++doXWRs9y7OXLoDr+fpXfpHRSmIxDXzjpd9iZTwhxiEhZHanbyA01NWYvekuzs/QrsbqGd28RnymDpneZrhunaE/x/xon7rZRHXBar2Bz1APa7x4RFqG9YDtyTkujD5E7jJqDudARXEEsgqEQiwhK1Xl6LuIqxySHAZ4J3ifyTkTtS/gvzwmM2ngPdFkSTQRkgpXnvswzdoJZvGA6ewBG+tX2Gie4sHeNapKuHn7Ddy9VeazQ0JVk3TOvJ8SXInuttrSzRcM6hHCEDdUHCscdPs4n2h0HUuJMBjRdgvGwy2G1RjfROpqAFWPZaOXQybVmKdPfIx1d4JGR/QhAZneFOcdYoXQklULhWJpFVzw5JRw3iNZsZRIKZFzwR5NFfQHJkj8C8kxeXeOSgrlKmWjaSacufgMkDha7LI6vsjTZz5FHxfsH71MzAMm4y2u3XiNQbXJ+dPPcOfudVzYwzFiY3Sa6wdX0TBFfQDzWJoz71uMzCScJ7cR8w5vHWuDipXRCUb1kIVOye4+BCElz+bKJhdXnufM8Fk8jpw7KhzZewZAnxNOhBwVHzyCQSrRYY+SVDAPAU9SQ1wh06Quggr6e9OR/tByPGuSK/idiCdMRjz17CdIdeLOwRvMY0bchN0HtxitZK7d/jI3b7xFzEIIEz54+XN8/v/9u6xujEEzXTjk5oMDEvuMJzv0cyXmewgjgqxRiaMJq4wnPV12jN06dVXjgqN3u1g9xbQn6ISBn3BmeIWnTnyQhhGpjzg3IGfFPZwi5ASxst/pyQjgBVSEysCpp9VMNihBZYf3DjMl62OyT6qCRzXjXMXmU89z+tkPcDC/RWyhn3WcO/cM46Hx7dd/kTu3bvH29e9w4dxneOGHn+W3v/TLbJxY4WB2j1pGVFIRmWLdGsPhKebzG5jUjMerhMpzYnwBS4KmltoNaMYG4QCrDEs1qXc4hpwaXmZ9cpbLGy/QuDEAUgfoM94XJ8BySR7KCMkrsuQHwtK5UyFJAYybUIFmWqc4V3KPxVmJAD9iORYX3HmHr0ZM1k5z8vxTtDkyWxywd3iLpy5+iJXxGl3e486dG7z8nRdJNHz8Yz/O6996HcSIqaX2EwTPfLGHqhKt4+btq9Qjz4mNZzixeor1Zp2+myK+ZdhUNA0YhlrESCQ3x+fMuF7n3PYHeO7MRxmOVnGusE3f9ULNO/AVzgcUh8PjEaBw/MwMNUNF8M4hwRFRklDasowKeB/w/jEJVYTK0TSbXPzgJxlvbnDz6BoPju6wvf00g8GIO/dfYda/ytH8Jitrq0wXd/ilz/9d7u29ymKhSBNp84zAmI3BeXJaUK05qtAQsmdYDUi2z2AwhrCLhECfIfgRVAvIDoljTA/ZWrvCc+c/xan60tJsBcCoQgYVMgnPUhEoXivUEgFHznXBAHHgFC+Q0pKcqUowcNnIMRKszMDgH5PIrHMBxhPC+hr7+T73p6/SRmN/d8HqcJcufp1vfPvXODw6ok+F+3Dj/qt0dh/fTOi6OSnBop8SbJfNlRW8nCVLIjSeLHtUAyXUGVAEB1kZhIpFWpCzY6PyNINTfOKpzzCSLYrVKgu7fXdxV4RizowIeKjA5UDShHlFMuBAc/mOSEHyTJWU3+W4B6LLeOcY1PWjH89H3iKlSsb2qacgBO7dfYmbt15GY82lSx8k5wXzfMDsKHF01DOfHSBphK+LmREdon3F2K+yXp9mOBpx1PVk58FP0eY+gzHM5A6RIzR5NCl1M6LPRmUDVqp11icbPLf1Kaq4RVONMTyOCu+W1HN1CAHvHA4tJs65Qn3GCvL9UIK5d8UxMMuYJpAlKSp46kpwPhEq9/isSUpNqAJtt0s2z/b6R7h0/kPU3hFtl8P9BfU4knSf0XCdrj0kLiDNK+7v3kJxdD1sbWzhpSHLPr2/h3NG5SYYRlOvENTjnafyDZJqetkHhI16wHPbP8KZ1acZDhqypSUjVlB1mAnLJA0SgroaJxXgESclmwKHZnAixcxpYT8VJRT31dvSoUCow4BKAvXjArA24wnNZI2DdId5bHF+he3Np0i6z739lzncW3D35h1m7R6LOcy6fSbNNouknD/1DH2nHNlVOhliDYwHDaOqwYLRpT0qhlQMyI1hmslMMRHWww5nJs9xZfsZRm4dciCTC2zjyqywnBEcike8YTnhCKgpYAUWIpbXTsEElRI3in0kLpMQynklMCGqBAJ4yPbon/tjUdLq+hb1eIif1wS/xtr4NDG2SKXcuPM2b9z4Dg8Od+mTI/YLhvUa4uDkyfM4KpQDtiYbSJySklANaqImcm5R6ZbZGMIgDxApA7nebLI13ubiyiUaHWI+kQxCqhEUfOGhl+wBwAp7CfUoCSdlwHNekmIeSlM1g6yGeLdMeXKQesgZh5IdiMugmWH16If0eNakagMGjnl3wNpoyKhaI+YHPDj4NhuTs0gc0/YHOAc1q+ysPUduKxoZkNwB/eRlpD7CjxzVoEEl0+YDahnh+gGSAzF3pNRCrtkcnGSrOctTKy8wtAbJBlnJJJJkEkqOhmZQFM2ppOXkjJJxzoHzpJxwllFVVAGBaO9ucg1TxZZ5S6qK+MLjcC5Q1QNCEOr6MVFSNZ5wcHidO/sv0sfMeGXEeNTwxtUv8tKrXyTmGVEq2vkU8ZEH+9cYrPRk5hzaq9QDpbaaqJkqwEDWOZo94CjfJPlIkCFVmhDSOuv1OluDy4zaE9B6es2knCEKPnoCDsuGaSRrBxTeXVYja0ZNCx8jZ8jF7/PZ0KxYViwtUYRlsaw6NMhy4HLOQEQ1gmXqqkKqx8TcCT1mY3bWP8TN3Ttsb7TkrmU8uADuO9zfu8GK22G0usX+/E2sekATJkT3gA07R+o7rDZyamnTgl4fIF3DyK1QhwZLxiiM2RieZCvsMFxs0T5Y0I86hGKavKtBjZwVW0I+gpU4kxnBOxBXNqsoOafi16WiNKFEkp0amhKWY0nn1MJdVyiKUwMz6kpAHCE8JmyhuqqJAs55xoMtqnqdpFe5cfsNDo9usrY6pFsE5vEm1rQseJvECM8aQ93ES8c8TUGEO3em7Jw6zWgSWPXr9NoDnvWVEVvhLPV0Fe+ENnWklKldJouwyIlGDLWSsZF1mfrppOyTksO7it53WDa8OnJOJayOEnNh/Ygs91UGQT1tzgXXS3nJxBVqV+Gc4H0Djwt2N53ex41Ooni21y/SND1vvfzbpH7O4WHHnfs3GA5G9HoP15SE2KyJqgvkwRxJFbU7QZDM9mbNzsoWjDyHDw4ZbtasN2usLs4Re0dTK//wn/xjfuIzf4Lc9fRL8mWVOxZeCW6AOIe4XPZKUhb+6DJJDaNQsZRi+jJlxuSsYEZKZc3KhbaCkYkxkZYmTkUIleAdBOdwzaNHHI5lTapHG+AX3N19gxNrmzitMMm0OmWvv0uUPULwbIbnGLqzVKzRzhSzIW1fcppWBw3DasDp1fMs9jugcOTODC8y6bfR6QjfC//sy7/K53/7ZX7j6n1izEvTFYl5Qd9n2hTpup4+JbJGcmxp44IUIzm1EDM5lrhQyn1xJnKGnEDj0lFQnFnx8LIQVVFXMuNrHwhOCJXDV47KPSbYnadi1u6hus/0aMpgeI/e7hF8zdbwDGPbpnZjkjoeHN7i4uZH8ZLpXMv62imaqiN3EfGOqHMGo47aD7lw4iSHbwXGfoiTjDSOX/jCr5LCBl/80pf4xJVznBvUON+QU4/3paZABiQJhkekPAQ5LIkyzpU8KAQxR05l/Spmz7CUyECfe8RlsnV4M1wIy4z4gJNEUwV8CHj/mDgOOc7RWhmvjBkOK+4fvsX+wS5dP2c+j0SL7M93STHRVJuoCslHRpMFTV2TtaOlQzuPk44mNDBdoT86SZMb2nafarTGV7/6Iq0f0x56xuPE7f17nDuxAiRUwOVEn1hmREfEFe5ccA7NHpOAKHjnwTtMlooxQzWV9UW11JsQyFlwVlEHIxELG08cVV3hvaMK1UO44KOTY1HS3ZvXOfvxD5MPXPGicqDrI/tHB3TukLgwNldPE+cznBuR/QGDQSIMlMP+AanvMWo0LVgZrDKpdsgH2xzdP2Rze1RIi13LK1dfhzQg25yxnOPg/j3s8iVUM2SICH1aUIWAmiNbWwp0hFI7QoDK1TjnCYQlCyhhZsSU8PbPnQDxFd732DLFNGiFwxBf2qtqj1sG/x61HMuatDjcg+QZ1CsknbO3eJ3p9B7rwy22hx/GScPhYs5keIrRwDFoKmLMHNxTpgdG2yXaxZQRE9b1PN2NGu2EehhwCM4Hbt+6yfpgjfboiErgJ//U55DY0veRvu/pNZI0I2LEFGm7HtSRNKJ9C9GDemLKBWlIywSDlNDY4XMiZl2CcxmzBB5c/S5CUZwOXAJLiPmSwO0fE+xuc3sbRWmqMc4yp048xZem/4DZXDk4yDRhFfNHHOrbhCDkxRFeR1SMie6QHB0nJyO25CnkaI3NasT97g7VcMgXf+UX+OynP0F7dIPrV99idWXIZz/2cT72dMWbrwoxF8gmOE8ysLyszEImJQi+IRlIFbFkpYYEQl0pba9Y7gtKLuAkkDQSXANS6klk677LUnX6btiioBCWBXHVIx/P4yFH9j0VNU1YJcoh3/jOlxg3E472FwzqgMYFwQ1wWjN0EzTVKIkkCe+E1cGIneEl6m6NkFeIyTMeb/H6G2+y++CIr33tRUSHbA/hT14+zSfOeujGbK9uENspOfWkNhL7GWpGr5E+lTI4ORXwNPUtsW/JqafvWtp5h8YWslGCFIWCbFoVerH2ODEqqUpIxSiIucuIa0oNI4BjCFUcy0xq+ym9diXimYdcOPscX/vWV5msnCa2LWujDRIHLOjpklC5NRNKmy8AAApbSURBVIwFg1oZDwInw1lGu1dAhISxoOOt66/wG1/5Gqc2J2ye2uHundf4kc9+mqM28dQHL3N463X8oCFrCzRk7QpS4IScS27UIrclPiE9hqACtQmeTE+PDw4vZdPqnMeHQJAldmclE1DECE5ISiGsSIMDNCpVUy2TFR6tHA/iUI+o6jGZRJff5NU3f5mN9VX296YkXZBJzLrbjAcn6buIrxLjumaoAzalxk+3keShdpjrkdRz7bXXOD/2hNmUZ5//GOOPf5zXv/NtxgFmdyIb25dJJEw9fU6gPd7XBZ/LJYrqnMPElwJSlst/15OWkFDlh2hWtC5s1oRbxotYboa1FJcyh6gv6Zri8KIgUDCNR6+kYzF3abFHlRscFaRVTq5/iqF7iqO2p5EJ3aJlJZxhb3qVnFoqNyb0Hu55moMPsGI7xHyP6298nSbD7Vu3eOv6LYbS85f+3X+Hb3/zK4jWPPPCp/jQx3+UwYkJ2b3rMSeq4Mk50fctqe9BI856usWceTtnNp/Rx0TbLmjnHX2fSColT0kanPklVATOHGKGJUXUkxNINrw+FEZXwArXwR59DtkxEVG0JfZTrIaYDzk4usn+9G1yjPTUZBx9Bu+2GNUruOjYWbtIug9DKm688zbbp89x4ZkVXv3a13n79hvUYUQrcETN8x/6YSpT1HpirPGV4S2AKyT9GCOI4tVKmiSBvlPcMvtQxOEtk8UxWLKC6spQGlQTKYeSB1soRYAsY4aFg4fzJaaVlwQIYN63DOoR6RiyKo6pIoqnn+8RmhMMhxsMh55czTmzc5bdu1NS7Lk7e4lQNawNx1xcu8BGOsvr97/B9ddvk9OMF7/y62xubHDv/i329+eoDXGjIRYCo8GI1pShL7Xz0IpMD2jZhJrhYiCLkrMruUU5F36CCSlHalGoKoyKyleIH1APKpwF6qrkVqmTYtKW+yEFgkihGgdPFsFbQizgrCkhD3lMAFZ8ZrF/j62tUwQ35tTmFSr7FvcP79PmllA7xjphMFrh6bUPsFOfZvbgHru3XuH227tMxsLQZfbfucE7ixrNQ06twL/1F/8SMUWcGCKObB5nhjjwZpi4QlhxJfErdYvCS0AI4mljJOFIJLwF6qy4yhWeoHN4CVS14F2FB1SKi15KQjoqpOB4eMQE0Z4sDi+2rB75XdLDI5Xjwe4cy1SQGc1kQuXPsb/YpbdD5hFC3bOzusOVrQ9wcfwMIVYMdwI7T1/ha6884LSfMO+nDJyxKoETz1xiUBUUIAMlaX1ZYcUVkpaIQ8UK3TcbMRoWHOkooRZJ2RAJeMvUoS4VJqtA3UAIZUNdZpQD53BSsvy8C4inoN5OES0UsmSCc2XtS6ZUwSHiwD0m8aTgAzq7jx1e4Sjc5bD9DhdPf5irV68yXsu0/YxnT/wQVzauUKcRKURS9Hz4I58CKu7ceIdXXzlibbDKsxcv8bF/9ccJJhRyQkGozYFKxnIhK5YKeY6siqrRL8sTGIapR3NHzD3D8QjDGAxHOOeo6yGDMMJJhQRBlixVH2pyTkvKdKSSQsxHBJPi4eUMkHE+FBxQHJYfE3NXVQ0+KO3sLZqdp1kZrOLrmuznqAknN7d4fvsFaqvJJNSEqvJ0Kpw+9TTPPf9JPvsThQCiWlznlDOC4hCyeDQL2bTUjBBDNeKlxH1yTiCJtAj0KWGpI0pCKiGbUfsBThrqOiBSFYqkc0Cg8gUx8AY+eHClSBUpkVyiuJGeLBHNpUyAvsvVO5acimPLqvBIKPVTE7foZnM03WBlEDkRLvDciU8wdgNi7N/VBCSHkxrvB1g26lCxiB3eKIOO4a0iWSamhOWErwKWl4U8vJDUSjGMbMS2INWLPEP7SFUN8FITJJTYTx3wvqEKJaoavAcpgXHnAjgHTsqaJ4L4Gsu51KFYUr6cr8ipLzPZKCUQHpckMu8TpECaPsDPP8h6PeDEcEA93mRwdImTzUly7vBUtP2Cg719pvf3eefmdZ594cO0lnC9IlnJTkhZEYW5zWEZDIhmsFBECkc79j1eHV2MqC0rlPQZi76Q6BXMO8RVuCW045oKDR4Rh6tHBK+F3CiCuOIVhhBKpFYjWECDEbtIicq/m+rilhCSIfJ+fpPrDybHVFvICBWYtei9m0zv3mBzscX5kz+M28i88fJvsbu7y6lzF5isrTJaafD1GmuntojJ8NHAHIaREmQtLG6SkcVKXlDMIAmkokt5yWUwMq5EZtuIaib3kew9dVMV2KfyhBCo65p6iT40gyEVSuX9ksTiAClVLK0kiolVQI/GXGaNailwRWER5RiXlZUfk5mUcgbnEE3kecf2xo+xKrew3GEhM/nQCfqUib0j9jP6uEBcQ98rOSs5W6krnpScDBOj1wzUBB8RtNCo1JOtg6VLnpKx6FpijASEnBy+GuKC0AyG+DpQVxVVMyTU41LXqBpRUdaeZEoINQ4hBCnt2jLjQjKC4HMg51T2RJrptcBLAGRfijE/YjkmSleZTc55+r6lb3tczsWNpWQB5hSXqYyZnA1nEGrIc6PynsViTik3UpQUgkNM6GKhBmcroYicO1SVxjfMY0eMCafFqZCw3DMhpFzqenu39Mw0UYURlpTeC5UTGlctZ5EWqpcaackUwgmWKOvhd4mSCW9C7vqSBG2CxsckfC6uRrxiDgb+qCDSDgKhzJTl4pxSwtThXEVvPRod2QmWIiqusIGdlUTiBFETThx9FkRL0jTmSdlx1LV0fQ8KUcAo2eSVOargC2NIPdlCqWG3ZDY4DG+gqYJKsGUuhQE4jzcjk9GYSWZIbRBLqqlopl8iHPRCNimvH7Ecj7lTxWfBAZYDioBXTDugoF1qS+I7DlOhwmFOqUToCVTZI0QsZXLs0KyIDOn7dqksT04dbVRSzMSup83FifChQhRqXyK5ZIc2BQFXqVBfFY65U5wPeK1KsSpziCq+EsQtZ5MJXh0qglvuj0QK/JQFLFkhsLj8Xc74o5ZjMndlc2kZMrGUCVhWsUpL2q7FUl/bbFGsWh2oYiItQKJiKdKblmqM4sgWsK5DNWGqxGxENWaLOTEpfQS0wEJeoR4o6g2clJTLqFAbSTNeM1ARyXitCxlFlCwJELBAkFDMmik5lg2qWukLItR1xbw9JARP35ctBKpLltGjleNhC+VC1fXOkZe/3IILpBxJlkqpNSk0XvEep4rGTJciecnl7lUxfTefSMmxAKOGkFKmjxHrhD5mNPc4rUqJMxlgUtJVYoLgSy5S7R2atZguIu9W3Xp39yniyg+Z+PzPc5BQ0rL0jeYlOyhU5NyjUmCmrIq6jPWOZBGVR+85HIuSupypl3UcskWipmVd1kyKxVTEPqGaiRlizvQp0feJGCOWM6QlNyFHVKFve9TKnr7ve+aLDrNY2vNlbfIe/NBDBp8rfOUZDhrCEu4xzThNRfkYtQfzCRcCXhzBuWUAtuyRUEO01OhLS9531sJodb3grcZLxJwRvSHZjgUWevJzcY+BPPklssdAnijpMZAnSnoM5ImSHgN5oqTHQJ4o6TGQ/x/lvqUy9VEMbgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "visualize_model(model_ft)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "ConvNet as fixed feature extractor\n",
    "----------------------------------\n",
    "\n",
    "Here, we need to freeze all the network except the final layer. We need\n",
    "to set ``requires_grad == False`` to freeze the parameters so that the\n",
    "gradients are not computed in ``backward()``.\n",
    "\n",
    "You can read more about this in the documentation\n",
    "`here <https://pytorch.org/docs/notes/autograd.html#excluding-subgraphs-from-backward>`__.\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "model_conv = torchvision.models.resnet18(pretrained=True)\n",
    "for param in model_conv.parameters():\n",
    "    param.requires_grad = False\n",
    "\n",
    "# Parameters of newly constructed modules have requires_grad=True by default\n",
    "num_ftrs = model_conv.fc.in_features\n",
    "model_conv.fc = nn.Linear(num_ftrs, 2)\n",
    "\n",
    "model_conv = model_conv.to(device)\n",
    "\n",
    "criterion = nn.CrossEntropyLoss()\n",
    "\n",
    "# Observe that only parameters of final layer are being optimized as\n",
    "# opposed to before.\n",
    "optimizer_conv = optim.SGD(model_conv.fc.parameters(), lr=0.001, momentum=0.9)\n",
    "\n",
    "# Decay LR by a factor of 0.1 every 7 epochs\n",
    "exp_lr_scheduler = lr_scheduler.StepLR(optimizer_conv, step_size=7, gamma=0.1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Train and evaluate\n",
    "^^^^^^^^^^^^^^^^^^\n",
    "\n",
    "On CPU this will take about half the time compared to previous scenario.\n",
    "This is expected as gradients don't need to be computed for most of the\n",
    "network. However, forward does need to be computed.\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 0/24\n",
      "----------\n",
      "train Loss: 0.5343 Acc: 0.7295\n",
      "val Loss: 0.3366 Acc: 0.8693\n",
      "\n",
      "Epoch 1/24\n",
      "----------\n",
      "train Loss: 0.4073 Acc: 0.8402\n",
      "val Loss: 0.2013 Acc: 0.9346\n",
      "\n",
      "Epoch 2/24\n",
      "----------\n",
      "train Loss: 0.3890 Acc: 0.8197\n",
      "val Loss: 0.1894 Acc: 0.9346\n",
      "\n",
      "Epoch 3/24\n",
      "----------\n",
      "train Loss: 0.4860 Acc: 0.7910\n",
      "val Loss: 0.3256 Acc: 0.8758\n",
      "\n",
      "Epoch 4/24\n",
      "----------\n",
      "train Loss: 0.4311 Acc: 0.8074\n",
      "val Loss: 0.2391 Acc: 0.9216\n",
      "\n",
      "Epoch 5/24\n",
      "----------\n",
      "train Loss: 0.4646 Acc: 0.7992\n",
      "val Loss: 0.1640 Acc: 0.9608\n",
      "\n",
      "Epoch 6/24\n",
      "----------\n",
      "train Loss: 0.5334 Acc: 0.7869\n",
      "val Loss: 0.1986 Acc: 0.9412\n",
      "\n",
      "Epoch 7/24\n",
      "----------\n",
      "train Loss: 0.3800 Acc: 0.8402\n",
      "val Loss: 0.2217 Acc: 0.9346\n",
      "\n",
      "Epoch 8/24\n",
      "----------\n",
      "train Loss: 0.3034 Acc: 0.8648\n",
      "val Loss: 0.2016 Acc: 0.9412\n",
      "\n",
      "Epoch 9/24\n",
      "----------\n",
      "train Loss: 0.3020 Acc: 0.8770\n",
      "val Loss: 0.2258 Acc: 0.9216\n",
      "\n",
      "Epoch 10/24\n",
      "----------\n",
      "train Loss: 0.3463 Acc: 0.8484\n",
      "val Loss: 0.2000 Acc: 0.9412\n",
      "\n",
      "Epoch 11/24\n",
      "----------\n",
      "train Loss: 0.3527 Acc: 0.8525\n",
      "val Loss: 0.1983 Acc: 0.9412\n",
      "\n",
      "Epoch 12/24\n",
      "----------\n",
      "train Loss: 0.2946 Acc: 0.8566\n",
      "val Loss: 0.2078 Acc: 0.9412\n",
      "\n",
      "Epoch 13/24\n",
      "----------\n",
      "train Loss: 0.3877 Acc: 0.8197\n",
      "val Loss: 0.2424 Acc: 0.9150\n",
      "\n",
      "Epoch 14/24\n",
      "----------\n",
      "train Loss: 0.3468 Acc: 0.8525\n",
      "val Loss: 0.1964 Acc: 0.9346\n",
      "\n",
      "Epoch 15/24\n",
      "----------\n",
      "train Loss: 0.3388 Acc: 0.8525\n",
      "val Loss: 0.2058 Acc: 0.9412\n",
      "\n",
      "Epoch 16/24\n",
      "----------\n",
      "train Loss: 0.2677 Acc: 0.8852\n",
      "val Loss: 0.1957 Acc: 0.9412\n",
      "\n",
      "Epoch 17/24\n",
      "----------\n",
      "train Loss: 0.3189 Acc: 0.8689\n",
      "val Loss: 0.1951 Acc: 0.9412\n",
      "\n",
      "Epoch 18/24\n",
      "----------\n",
      "train Loss: 0.3015 Acc: 0.8852\n",
      "val Loss: 0.1847 Acc: 0.9412\n",
      "\n",
      "Epoch 19/24\n",
      "----------\n",
      "train Loss: 0.4257 Acc: 0.8074\n",
      "val Loss: 0.2089 Acc: 0.9412\n",
      "\n",
      "Epoch 20/24\n",
      "----------\n",
      "train Loss: 0.3590 Acc: 0.8689\n",
      "val Loss: 0.1813 Acc: 0.9412\n",
      "\n",
      "Epoch 21/24\n",
      "----------\n",
      "train Loss: 0.2702 Acc: 0.8975\n",
      "val Loss: 0.2482 Acc: 0.9216\n",
      "\n",
      "Epoch 22/24\n",
      "----------\n",
      "train Loss: 0.3063 Acc: 0.8730\n",
      "val Loss: 0.1837 Acc: 0.9477\n",
      "\n",
      "Epoch 23/24\n",
      "----------\n",
      "train Loss: 0.3738 Acc: 0.8402\n",
      "val Loss: 0.2212 Acc: 0.9281\n",
      "\n",
      "Epoch 24/24\n",
      "----------\n",
      "train Loss: 0.3151 Acc: 0.8443\n",
      "val Loss: 0.2041 Acc: 0.9412\n",
      "\n",
      "Training complete in 50m 21s\n",
      "Best val Acc: 0.960784\n"
     ]
    }
   ],
   "source": [
    "model_conv = train_model(model_conv, criterion, optimizer_conv,\n",
    "                         exp_lr_scheduler, num_epochs=25)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAGkAAABeCAYAAAAg/TovAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjAsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+17YcXAAAgAElEQVR4nOy9ebCm2V3f9znrs7zrvbf7dvd096w9MxotI40ALYh9EyAkDDHGMmBjKiyVEIyLuAgup5xywIFUiJMqjBMTKxiCjFkSjBxhLAQ2WhkkoW1GGmm2nl5v3/XdnuWs+eNepdqylhH0BU/VfKveqvd5znnP8v2e85zf+zu/874i58zz+E8b8i+6Ac/j8+N5kZ4DeF6k5wCeF+k5gOdFeg7geZGeA/gLF0kI8YtCiJ88ev/lQojH/pzqzUKIC38edf1Z8Rcu0s3IOb8j53z/58snhPheIcQ7/zza9GfFzYPwT4tbKpIQQt/K8p7HEXLOn/MFPA38BPAosA/8n0B5lPZVwGXgx4HrwC8f3f8W4IPAAfBu4MGbynsI+ACwAP4l8KvAT95c3k15zwP/N7AN7AI/BzwAdEAElsDBUd4C+J+AZ4At4H8DqpvK+jvANeAq8H1ABi58vv4fffZvAh87avOTwA/elPYpDn4MuHFUx988SvsBwAPuqK1vObr/48CVo/IeA772c9b/LEX66BFh68C7Po3UAPzMEUkV8PKjxr4SUMDfOCqjACxwEfjbgAH+8lEn/iORjj77IeAfAQOgBL7sKO17gXd+Wjv/F+C3j9o4At4C/A9Had94JNyLj8p6880iAX8N+PDn4OB1wD2AAL4SaICXfxoH/+CoT998lL52lP6Ln+rf0fX9wCXgtqPrO4F7boVIP3TT9TcDT9zUQMfRzDq690+A//7TynjsqHNfweFIFjelvfuziPRqDmeQ/gxt+g9EOiJvdXNnjz7/1NH7NwE/fVPafXwBM+kz1P9bwN+6qc3tze3kcJC+6rOIdOEo/esA82zqe7Zr0qWb3l8Ebrvpejvn3N10fQfwY0KIg0+9OJyFtx29ruSj1t5U3mfCeeBizjk8i/adBGrg/TfV+W+O7nNU76f34VlDCPFNQoj3CiH2jsr+ZuDETVl2P62dDTD8TGXlnB8HfhT474AbQohfFULc9pnyfgrPVqTzN72/ncPZ8P/X+2l5LwE/lXOe3vSqc87/gsPn9VkhhPi08j4TLgG3fxZj5NPr3OFwNL/opjonOedPEXXtM/ThWUEIUQC/yeF6dyrnPAXeyuHsfTb4j7YZcs5vzjl/GYcDOnO4XHxWPFuR/kshxDkhxDrwdzlc8D8bfgH4ISHEK8UhBkKI1wkhRsB7OHx+/4gQQgshvh14xWcp52EOyf3pozJKIcRrjtK2gHNCCAuQc05H9f4jIcQmgBDirBDitUf5fw34XiHEC4UQNfD3n2W/4XAdLTh89AYhxDcB3/AFfH4LuPtTF0KI+4UQX3Mkfsfh4Iqfq4BnK9KbgX/LoWXzJPBZ7f6c8/uA7+fQEtsHHudwDSHn7IBvP7reB76TQ+vtM5UTgddz+Ax/hkML6juPkn8feAS4LoTYObr340d1vVcIMQd+j8NFmpzz73BoWPz+UZ7fv7kuIcR3CSEe+SztWAA/wqHQ+xwaGb/92fr/GfDPgBcePYZ/i0PBf5rD2X8d2ORw4H9WiP9wefgMGYR4GvjPc86/9wU07HncQvwn5XF4Hp8Zz4v0HMDnfdw9j794PD+TngN4XqTnAI7Fa/2d/+3Lc+u2cWHJboDpcJOpkAS/xJrTbC6/htxqDBk7uINyfQ2lJIM04JVfeQ//+Le+HVtaViEyNgMGRc9OzgSvqFaSE5VEibux7gJba0/Sj57E7Y7pmiVrVjAZ3U55/dVoI4hOY22FLgxKa4qRpbQFW1t7bNRD2pUn5YzWBUZpXvoNmfVTK2b+CT7+5Hv4xPv3eDQ9wYa8k299+Q+irCF5h5Al0lg+dOXt1FWEDlLsuL635H/9kV9/tl90nxWOZSZFNPQC6xVl9Li+xQyHnL7zJTz4JQ9hBiuyLzB2nW52Fdkt8Ab64YqPPnqZH/qGf00t7kALCDmQoyJ4yaguuPfUlI3plNnVB7hyDcZXX8VGeAiyR4pMNJbTGw+glYFQUJQFhVFoJbAlqAr6Zc9aPaDvJD5kJANyjIS84tQJQROucfHSZcy85v2LxwhtSxt2+VcP/zMKOaSsp4wHEyaDCQ/e/tU8tbPgie09PvjxLR559PFbzuexiCSkRxAQPiF9Rig4f/cLuPPc7RRac+ZFBcPxhM45khAsV0sWV66TlMDJFZ985gne+NU/y1/52p+hJbDvHFJnhlIhraKWJwiuoKo2yFFzB68iKkVtBNmDimNAIXQgEVh1HcJKspCHHZaalUt4H5BCEnNL5tD1du3qkv39FWWYsLNokFnhncS5FS7NeO/HfgcRBUSJkQXnp3fyl1/6Q3zf17+av/EVL8eFz+k8+FPhWETSVmNEhR1tcO7Ui1kbnyX2npwdz2xd5t997F108YC+C0ymm5RFwe1nJrS7Lcvg2fctT1x8iu56yXe/5uc5vf7FDHzPluvJKrLd3I4Uko2Tm8g8ZOspwQZTKmMZmJKwM6SwGkVBXZSsbQyRMSF0RgiF0BA8CCGQUiIRVNUIqQyCmsngJTx18YP8sXuS+oQiSFi1jias+PDlh/n1338TrfNsXdrGdYn14ZAcv5Lf/sB1vuj0A7ecz2MRqRSGM+fu4I57X0Y9PYlPme0bO3z4iU9w8fGr6C7S+wWT8YAQGoRM+Ljk3BmLDJk917HdtcwWDf3S8eDJ72JsXwCd43pnCN15imKdy5efoq4mtN2K9e6LKGRkVGzSLiCQySqhrIIcCG1CZY0kYauKWimMUQg0tqgBQWlrOnfAhz7wqzy8+wQ29ygDUsPKe6JPuOS5vn+RRz7wbnJIbF3cYnkQcJ3njV/z1zk1PfF5+flCcSwinTp/Gyc2x1iVKFSi39nmmctPsNzZA9GRZcPO8D20zrNatfSNY393H20858/CIDquXN9hlju2tq4SWXLfqe/mDa/8r6nCi0mzkhwgNLA2qQleo5p7ON2/EZstRicKZbF2cLgNZwvkQJKyxxpQysEAytIgDZgiE3Oi7xv+4F0f4pd/5z0s9j2uV1ij0NYSo8I1HTKsSLnlbR/6FX7xzX8f7wLXLl8nHAi2n5S89KVvvOV8HotIsohE49nf3+b6o5+ApiVlhwiaHD1IEOIAVW4zKAdMRhWjwW1sXZ6zfX2PtVHNqemY7b0ZnVTs7bT4FDi4WvDiC69G5gpbgNGKzkXGxTrLZp/cnmG9fAVSGKJ0IBwGBQSM1FijEdJipKRSCmsrykIjsqEuB+ScqIsBJ0yFRRO9xCCxRULIzCoHfJIo4uGs8tv8X7/597hy6SqXntpjtUgsD9yt5/OWlwisXMv27j5tu8tA99SiRAVFCBEhJCkrQhRs129jNe/YvtHQrFbIrAlekvwemycst62v0yXNeLMiZygLyWKluOcrAnt7M8gCKSST8QTXSWbNLqI7CUVBDApjDF4LimFJLkFbhVUZaTPaJKT1ZJFxvsOHHmOG3HnPC5iuD5kaTZETCEVRW0wpSEmQfYvTid44Zr1iv53xex/5J/jRHDvsSL255Xwei0jNYoWRmdoYiqrGmgqVJXUMxBwJBFyE4Byn74TUZ0KA1coTl4LUjNnd2WM6LFkflbREyomkz5raSNobitd9zx3EJNne22IyWePM5v30K0G3Ckgf0MaQs6RQFkWkEJnKSKIQSDQUBVIkilowHFm0FUTZMhpvsFEXWFmClyQEtY6UWoEIJCGICJSRKB24cO5L+K5v/Huogymrfcn+bnPL+Twe624vILqMl+DNkKGpUKKg8Z5BJ3AZTk5PcFd9hpOnH2C8qfBdJHWW1fJQyHGxwWo5oxYW1UPsLEkIUug5uTHm4lOOL/9LFzhYXKYJe6jQYeWIvtVEAUoZbGXRBgpVo60CA1VdIrRgXApykalKizYGa0sgIpWjiS3DcgOlTiFFidAWO87EMuFzppIJJTf5iR/9Jb7swe9ndm2KUgO6RuCfKzOpa1fk1qNziUXTk3B9huhZOE/pA+M+oEzBudvXKE6ew3cBcqSuLM2iZbWYMyinzJc3GNkSUyeMUTQp4rxnfTzgYLfl67/rZbS9Y295jVl7mb5fYQsYFIahNUihQSWSBKSmUJm6VmQrqEuLKhRlrRHCk5zAtS1hcIqquo1JfRsSjTJQF4qhNmi1RIaav/2Gn2Hrk4GqGmKtxPUda+sV0+n4lvN5LG6h0DQsGOFEd2g17TeksGS3CEy1Q4cxrZXI1vPWP/oNXv3SH0UHz1MfeYYkJoxHNdFD1y2pdMXOjQUnzjle+uI/4gOPfgtN7xkOYK2w7F1quPNVhifePiFEQQqJGDLozNI1jKylsBJTliglUKWiEoDTBOnJpsS6TA4FZVVgdWZ9cjvGDKnkDWZNj7IKMbbI1vMDr/gFZk81XP54QipJv2oZjmqCz8xmC5K4pR4h4JhEstGSmhmiHNLnFZF9TNdDWTExE6IZsXAdbX+AFIJhsWBtfIr2/AHeKRrnGNiMbzT1tGD9RI3q/nc+9uEGYxMUkpwT2hvkSBIzvOwNYz70lpKu85y9TbLcj6AkMUmoFbVUZKsxJWgpUU4TnEDGCJXEzTtc6Fj0HVl4hIm0LmBySZEWeFvxVx/4H7n+AYdkyLAeMJ93lLUiOEHX9Qgp2Nvb+fwEfYE4FpF86Ig9uLzAqoAYKWJrqWTNdLhJNiV77YICmGzWvPP97+SrX/Et+CS5/tTjhOgJvSVZxe7MoVPPtd1dVNri3ocqjO4wpaGVPZWxiKqnaRe89FtrLv3b21luXyWaBZU1jE4bjM2kJKkKhZAaJaGqBNIKCJIUBfVEIoqaR556NzvugH45J3SQ6zWCGfNa/WN012E0tBhb4lygrHuaWJKXCxILcoY+PkdM8N735KImqwplDcOi4tT0FGtlzaSeMq4MSoEoLOPBEJ8u44OnrGpOnB2SImQiMTuKASRdsDOXqMkFjLyBzBJpDYO6QoiIaKGyChdbpvcc0OysIQuFUBFjNKYQaAkxSlTKSC3QpcIWGlVLbKkQOqNU4qr/ODl2HMwalrMDLpz6cr5++hPIoKmHJcW4QAnB+saEerqBSRmXVyhtSDoShbrlfB7PfpKuMaVhnTFlX1DpDU5unGdUDfF9f7hAi4SsC6rBBptnLR/4yEe487YzjKs7OH3/gEQguITJkeFI8kVffBsvfuHfIq5+lq6bkTqBEoJqWKJ1gTAlVimquw64/VUHDAcGXRYY67FaIyVoEZDmsNdGC6xRVFZibEZXkugTZhAwA0OSmTe89vt50elX47uCtY0BRfFmqkpQjxULNwfdY4aRuoSD+YxulXGrxS2n83i2KsqKQhsKI3FdovOCYiQYVFMa4WlTwKceNRyiixI9FFy98gmevnEVYQ2TeB+nziumJwV9HyjKTF1+DxHDxj3/gPtfdi/RdaQooQddKGQSKAxaZYoTmbWzNcZIVKmQRqEHGlWCRKGVRGqwhaQoLbrUkAKqLInaY2rJt33t9zGoNuhcyXg4YX/rV/gXv/Ywps44melcJAZP2zXM5wkrKuZ7C9YmnzMY9U+FYxGpqC0+O7q0xJNIypCEBmXYdg3P7DxNHzJ6chJpNNnt0i5v8OGPfoD1yYieQHS3kQzooSGHDt8GJIFuVbNY7XLuwglizsjSoISlKiVKSUozpNYSVUNMnlIZhJHU1lKXFdIkBBmjBFYrjITCZMqB4vyL1imN5Q0v/n7GxRRrCu45Gxjan2UV4PZ7LuCSpvMdo6mi9YHcK0JMJKEZjse07XPky2wpK8bFgGQ0lAWqKIBMjgGJx2mDUYrCDCkldIs503pI18x5Yvc60/UJo3JKXE7o2xXRCqL09F1CikjuNJmO82cmRNejlACpsVajjEYKhRQZUxYIpSiVQmtBVhmlFFkKhBJkEsJqlNRsnBxw4/on+M8u/CglA0aDMcO6onf7jDd/jMbXvODuhyBlykKQBAxKi8sRXdagIkYqnD+45Xwej4M1J0bVgDvXz1KUY6zVhBzp3QKyw5pEMVjHCsWqc+xv7WMLSb+/y9OfeJRV19MjqYoNUjOkXe1TDjS6jMTk8VnQLByelvUzG0gUJImRBmsMpi6oy5Jz90xQWpGzJJOQJDIBkSIQkdIgEQilsKVkff00g8GI8WhIVdbUpWJ9+kL6vOLeC1/PmdtfS6RHGIFKCZck1kIlIzJEfNri9F3HwOetLxKaFFGiRKv6kARhERl8zAyUxioYljXaaA76lp39fXp9kcqOoE88+vTHKKsBIXhqM6DZOsHe3g5dWKAsIBJKlgSfIPesn5wgIqAMpdFUymKUxipFBLLIQAIyUkpiTuSYySSUlAijEUIxHgyZjNYYFhWFkhhTsPQdB4uIMBXCJMbjGlMYfM4Y42n3O5rVAjtsGJ62/OH1X7vlfB7L9ySd4IaPiH5BiiBXgVZKug56nUAk6sGYLGDezNnurxD0Lvfd/QAXH99iKhPXd7eYViOSSlRBUa42YO0ii+Uew9GQVCSUKSDBfLXH4OQY3zRkDEZpMi3ZWsqoiMkRUkIjiLFDKEsko2ICI7DqcKYNyyFaasgJFwOx86waj0oCaTRSRXwIhOCBAMIzXBPYgeUdl9/MarWDC7c+jvFYROoINN0+wWVs3zCTEik0UQZUpRCiRJ1ImNEKkRacvF9RKc1KvZNCvArfOfZuXKK+60UIoRhNC/AwDC9moR7DNR3aKmTKpMGAwlQ0sxm6KMgpk03Pb//S24lqh2/7ju8AqfDeE4hkBFZmhI8Ie9h9JSRKSgwacqQNHV3n8SkAnqo2BH8YE4EQpC5gtGMVWuzaLv/PR95EUXlC0qzcszlO9YXheA4ia4EcA64FDd1wxrQCYaBbOKwsGVaerPdom2coSkEgMktPs37mS2n2BDbC1Wc+zv1n78N3PZnEcjnn1PCFdLEl9pdZ6UhsJaXNFHXNfG8HVxQYa5nUJ/nVt7yZd/y7P+C/+rEf5razdzGf72KsQg/XSCqjAKskpS5IBJzvmTULiIngM9kojFY4n+miJypB284IqSXKxB9+5FfYyxeJxYyuUYRkcN3qltN5LGvSxn0Na3c2TO7okeMIZQtmQYw9ZYYUDclpDuYF+zcCs/2S5obCz09gT17FGMdq4alyZsc5tLLYqiJFyWK+ZDpcY7N4Cd5FfN/RuAVt11JPJnTNktX+Lqqy/ORP/X3uGvX8ydveylMff5iyLKgMvOOXfp5/+aZfpigE1tSsmm1miwNmqxkEBwh0YVFIXMr45HG+Zb57ndDMCbrhzQ//FDN5FWUkFmhwOL9ChlvvcTiWmWTO9LjkcAeJlSthp0Q4QdGWFKICW+JyhafHtzA0U2qtkWZEFtucuu8UVx5Zslpl/LXHGd1xP8aD1BKtNMG1TCfrvGjyaq5fP2CZP4ZPGZEqhtMpWgpC2GN37wYfeKbnsYPHuftFd2HY4P/46Z9l4QPF+EV88D1/xIMvfwiRV6y8QSRQRYVC0XpHSgnnOrx3tIs92tjyxzf+NXPzCAxb+tkQYwdYPULJXTpjUS7dcj6PRaR5FOTdMXIX4n7AzktsG5G6OnS5EDiY7+FEgnS4U3toYfUsYokqH6ccvAy8pxoOufj0Y9x++wuwLhKCICaN0hmpAlpaHrzzS3n06p8cWlnG4K1BGkdanOGFpxRq03Ojehvq6nv5+h+9wKWndnndq/8Oyc25eOWj3H7HSxHNDFHUaDSBSEoBcqBr5jTR88yNp/jEwbvRoxabNUXRssganUuiqqg16BgJ0t5yPo/lVMX3/ua9OS9O465k9g5uUCTB/fU5Cj2mC0soNU802yy6fXB71EXN5uA8mho1Osltm7ezUZzj4vsFOo2oRxWj6ZSTmwPWzisigZVbIIRES40SkkBEyEyFIqaAiy1XHnUMBo4w+OfcqK9z/x0PMNubsZo59p8ZcPB45FVf/no2zlygqKekCFpIPAnnPW234uHH/j2Xm08SYkdWBVKv8PoGnbtBcwP6ZoipKhAzwsKhG8Pb/umTt3RT6VhmUhs8Vu/TyEQX54zkhJQTIiSKQjMYDHiiW9C7JUkISi9JWSLRrI03sEmTy8gLvvwcu08lci7RZY+Xhht7HmUS2oCUAp8yUh2Z1yT6FEnREV3LqbsF20+c4PTJH+DcuUt4/0nms4t0fWDvmQWXryrs+z/MCx7oedkrvpkr155BK4VQGrJAyIKvfPC1eP91XG2u8I6P/g6BFUKDLSKuhMUqUMaMrEowjhxuPaXHIpJbRarxDLNhYGbY8S2nc4NQkpA0MhiUGRJzRCtLtiO02uShl7wekybE+RC5U9IuHIXJGFuidE8kMFA1po5YIzC2QCgJCBQCYk9IgRgEUfa0TUt14lHe9p4PEopnCMOnUM6R5Jiu82xvl1y+9D7C4oBXvvpb8c4hihLIaKMwGOYLaHZb0vx2Xj34biZrIIbwVP//8ofz38WqyKpxrJkKaTPl4NbbYsdjgrtIDILRWODWFP1Wx6Vmi1rcYLp2P6ltSH2LB04Ud/NVmz9AoU/SPJ2p6jFGaBoapE0MR0NC77BjzWCoQHmk0NjSYrRFIshSkGMgoUhdj7EF3heIuODxxx8l2V1cugJdhXQVq5XjzjMPUAW49+5Xsnm6AiKnNk6x6FdIVRya3kKgZKAeGaSLrJqS+Q0IlxWmfR3f9+Lv5tGN3+FtD/8GMcK4WKOubv2m3zE97hR6KSjXW8bnKlayorwq0cnQJnDJU4YN/vpL3oRpptiyoGtmFLoixp6sm8Mw4MEAqsxwLAlCk/HUZY0pFVYZyIngPVJJRqMB3gdEzCyaGfuzPebzOc1qyd7lBdeu7XLqriEMK86eegmbo3NMX1wwqARr63fj+pZ7zl/gQ49/ECPB2gJrNdktyXpC7hp89iz7BkSkrAquPeaYpm/kr1x4De/vfw0XH0HZ4pbzeTwxDp0mEEhNoh5k9EmDu3Z4EgHvefC+11K2L2akz7IXtmj2G3TpsUpQDyyIzOaZzP0XHuPGXsd0VPHklQskYZAkui5SGMOJ6UkEghgdi77BdS0HiwMUklE1wYeOuy48yLve9Qi+tZxfe5Dh5immVUVQlkJETDE8HAzWkBMQM0lFvPcYJRhNh3RNpFgrELogtYE+CtyqpVn2lHbI5onzfFX4L+g3H+NdH/q5W87nsYg06gYsdcNiaTC1R48yq4nlwZNvZJgfpFqeZWdrm1nxDOOBZDA2yHJEJDEYSaTWvP13f5oPvjcS3AGj06/k677xqxDKQM7kFHDeMZvt46Oj846iKMjAaDSma1Z0zerQozAa8XWv/WY+/PD7uH55yRfd8xBKBAqjcDGTcmax2Cf48yx8Q/aBNiWM66EcoAmcPfFRlsW9XIklJ+/cwC3m7M+GoDyun3P5SoOk4GT6Yl5x2w/fcj6PRaRBWzJTDVnCcmWY1GNed+9P0e5U4EdQ9pRTRUo9qVRoYzGVBZmIIuK94JVf9hOUhaUcCx59+Dd4/MknEVpT2cM1SB9G3lNITVmUxBiQSpG6FT70IMCUY6RP3PNCxfkLp2n3FhSDEd7tgRlRKJDqcD3aX+xSKMUL7nuQy9cu0eNJREL6JAd77+Tg4AFyEviuwaMZTxSDQnD5aktRFDjXcvXak9x+7qFbzuexiFQ0BTl6tFJ8Sfnf4D54guVwSB8aXD9HB8FkbYBAUZqSiCMFj1GG0ahCW1g1Lckkgrfc/eDrqQc1ujj0CgiliCREbOnwCCQGgeuXLLsW71uUGaIALTqW80hVTjhx5924sGJv5hFZUlYTVFHhk2QxP8BIRRM847V1SlOy8i0D+SgH2zVBVYxrSV8XLA6WhC7Sp57xsKBrHZWuWM0jz1y6xOFP8t06HItI1fQE9UHkweKvkj90L1p2bO1eZDKZUI8Vw9GQnPrDL4FKsTEdknKPDx7fZKKLBB9IvWNyZkKQGqMOTWPnG3zTghRHjfdgFKvoiCGCEpTVlGbVQcrsrfYwtmI8Wmc0PsHW1QXGHgb0F0WFkpaqrlm2DVXTcfbkHWwv9lj2C1Lo6dycrWtfx+S0AqGQnWc0LnC1pB6UXDnYQdWK1c6C+apjNKhvOZ/HItKLHnwl1XtfgLsoaPJ1BgPLaLjGcDDBDgLCtCz2GlgWDKqaA9fSxhneSe64d42yhjQ3VKbGxUDwidlqh8JYIhFbWkJsiMJgdSSQaJsWaS2plUQTOX1yg0eeeB/WlIwHIzbP3INGcNl1WD0iq8R8OWN97QzWTjltJ8zmB3QpkmOmMAP++L0fYvfSv+EN3/ML9D4RYiC5hkCitJCE4ty9J2gbwZIZy+469bC85Xweixf82p88yO7uLmjHXRfWUMrjXUvInmFdUak1xpMJW1u7bF2/wYnNU5y76zz33n8nZV0QU2ZYFcS0oPeZ5UGPliUuRayVROeo1JAYI22vaBtH6CMiRigjOjkO5k+Bs9R2gpU1I1NgpcIaS1kUSGkwWrM7u8pidRiXUI3HZBdZLfbou47XfMWXk8UGO1sz3KrHqIJqfcRoNMZ5T4iOorQMRgZRDHnggdsp6tEt5/NYZpJE89CDD7Ba7LN7ZYFUNeUYNjamVLXB1p75YsorvnSCYsxgPRJ6RYyB+bxDAoWwuJCxpmQ09CyWjulogIyR4BPzdkUpBT5n+iwZjixPPP4hst8ikrHVGbIaU5Y11mqsKWnjEq0tAkNVCsgK1+7w2NZbeODcX2KqJ7jUMShPMt9bkr3itd/+D0lSsNib0Sw7ehJrkzHj0QmcWyGT5tKTV5iMhkRVUXbPkVjw0cQhVKBUawxOnKHQknJcMFkfksUKKRJrU0nMGu/nXH7GQfSUdUWz6KhHJZSa4XBMDB1ZFFQFtAtPlhKRMqHrudz2FHWkHsM//p9/ks0LpxiuDVDBce/Z84w3RwQJSR66eK7s7SGlRUiJC5G6rFmtCpKB69sfI49fiK4HrNU17SIhosZ3kSgDk8GEzgVSs+DK0zvk0LJ5/jw2WzZPb2JNxfYlR+e3bzmfxzBnqgUAAA7vSURBVCLSwW6kVIdHVQo9wNSJ+cyxd3AZU3rqkaZrBVLAYDJgc20NKQWm0CwHc4alYW+ngS4TkkeXNYoCKaFpV8x2tok6Mj0Recc7f4PtK5+gHoFWhi4nusbxsuk6lYRaVBTSklKicy1Ga6I7DDtOIZJRDM0JHrn0dt7zxL/nGx/4a5x92RcxU4atrX3ImdF0QK4ajBlTlpD9gKsX93j4sU9SDgSVXeOue+H83SWPPfIc8d3N69+gvut+clvwgUcO+Irp9yIUjKsxQnpqO2VURmyhKMtDZ2hODc2ip2k7XOsPo06lxkpD8I5l47hx/QZdWlEN4d2f+Keox+f4vY7FfJ8T5+/CDBRORExRIwhEOcaR2BhPaGMD4jByyYcWSAijqKsBWk2YJY8TK9764X/Oi174IJcubjOoLDFJdm/0SC2p7FUGkw2szmxsDpmMJzz11EWyW/DBh2csFgtuO79+y/k8FpEWbU9z+UNUJ09w/qGK3732d2kPEufHL+F8+UKm7j6KImP7mkuXDiiGBdllQpLYMpBcy43tGaZM9Kml9T37k/czP/1JxPY6YsexyNcx/YrlbEHIIwaTk6hCo4icO72OQ1PnjMuJ6domuX0XSp6kxaNLQ9f3qJjY228YnN44PDcrFKrq2V9t80H/JsaXv4y10TonTpzEKku3KuiaBfs7W9x14S6mm+s0y8zVq9dxrsd7CbG65Xwez0zau8GI05w8P2I83kQPK975/t/lo+kqH139K6rdNUbTESfWThLUHLdtSSKDSpgsWe5vc3V/ie00eiQoNxsGw5a+G2JmEhYJpTxki9IgK4MsC7SRmFGNVBNiEqQMD90+ZKr3+PClfUI+gUwGUsYaS9N64lyiTkVS8CgFRlo+dumP2VLv4fLZ93D7tW/iYP8+NjZOIbNivLZBlJJ3/uH7mM9XlLbi5V/yQtzyDI9/4hKXL+7fcj6PZ03av4ouNM883fDyl21wqlqjHp6kSh1L3bGsD/BpB68vsj5qWaLpdm6jSAaxSMyXBygM9bgkDhqi7FnMLEU7plssafw+VhqSEajJOlN7jsG0Ip0wbJZjrBwju4wdKX7vrR/klS//E2Txg4i+QeRMHzMpQVgehmlZaQhWMFAVWsP7nn4L68UDPDQqeGv96zC3yI/ezeb6iygXa6SVoZabiGqHVe75kw93TOpT1GNFVU5vOZ/H4wW3mZ3ZZaI+Re/3KaoN7rrnbq5fuoQwmnlzQOcCZd/ByKB0IHXt4a/7REEfAroqMAODNJYuKcrVECM3UJN92v1MdAlEoBgYzGgIteT02gRNgXQSnyI+Z9Ynj3Lj4DUwjgQUSYCSh56LbpURMR9GIwmLItPFgKo9b3zlq3jiEx+jS6Bcx+Lg43R+m1G1jphaVqrl7G1Tvu0F38Hm6G5+/ufejugKklgAr/k8DH1hOBaRhGoRMbLfBj54+SL3nxKMi5Ll5gaD3rFsHalrcI1GR8VQK/ZVSxENffCkDCr2xNRCzkhnKc0GEzsmDhzzpcQvemR22PFJZFkwGZZUXtN4j0QggyR4xfjs63FmDWLGYgm0pJzJwVBPIi5YWtdhosR4Tydbglzym3/wTl54xiLnib1Vz/5SkAtP0UtMpdCFZhUXzEJLFbf44R95FVbXhNDfcj6PZ/vcdwQJwffMrlxlWxqq2zYY2SGzbkblDKsgCUuB7SqmJvC0cXh6QvKgM5WUxBCIEpAVhbJo7YmASpaULFKCKCQUgmwUfd+xtzjgxOAMNCVxlGl0Ta3AKIOPPUSBFoacHMtZoPMJ3S5RuWfhe1zsUbLgt3/tY/zKfuBl3x8wxRpnpkOkyIgEJkRyaohN5Nre0yiRmcmrSKUxtua+W8zn8Xgc8pC2a1Aq0O/s8nTU3DmYMBkVbLc9oT/8dZF2EfBNRVlLhtUBrpuzlIqNashYSTqX2Bcdo8EpalvQrhYsFzOc6xiMa4I4PCA2OlVSBoOLjp3LC+580YQmJ1ISBNehRiOUlCyXEWsL2n5FkgJjJToIhJoTJbgUcTFThIa7T0+56/Un2a2fohydxktJT8RnUC6Qh9Donn23YM3P2M8RKTwT9xn//eDPhOPZqtBrhJXDyx6jD1ChxMUGGQyDsWaxe/iz9Q5YLSSNhFLALAWkiqxHhfWROS0yCWTWuOwI8yXxYIfoPX44QitDMSwZFkO89zQ+AgVWDWhVBAc+Z2LsUbJEGwU5QdTMr69YH5fMo2QRl1RWs1pohgq0Khl8+4yd8hJmbxNKiYgFyktk9kAi0WMdtL5l1S3xZKSMKHnrt8+PxcE6rCwKRVoJdC5oheTq1g1uuBUnqzUGlWGiFVYr5rOGtDDYMKCLLeO6xpaCHCPLxQKba4SIED30nv29FaFviTmjq5qqqGnnS1Z7M3afukHolzQrR1xB10Klh8Tu8NxS6BJCCASJ4bCi7WE4sSxWT0FRk7LFo+nj4cHaIoGPHctmQUgF48GIdWkRSSAidMmzcg1z5+hCT/Kevrv1a9KxiOSDoxKS7AxWllhrOVguWbkDMj3j6RibFYXSdMFDiEyzxihNVShimdiJPTEcheyGgEKgiwqhh2hliCIRUqadzdnf3+OZrW2WrmO/X3Iwa1CywHUNMUHXgUtQlRXOCRbznt4FXOyJXtDFGSYJknPkLMBHIoKozOHJclszlppTSjFUilNSoKUkZ0WfE/SeFDNtVjhufZjxsYiUVIfQgtIkTHECJQb4uODy00/Q9D3TQYmyGpRikRZ0PkFM2C4SZMOubziIEQhEIn12JBfwWCCCsVSyYzoYkQrF1nyLZtGxWMwJ/RKNJuZMaMGoGkUCH0EIPJHaFiwXC0Ibyfkwxm5clSTp0DJBaFHtAoKjGqxxcn2d0WhIXVumZkApFaOsIfX4riOkhA+Z1DuS87ecz2NZk3KxxJqS6CJJGmIC383oW0/je5AWuVFSHqwISbHsHVX2xGRZ7S8JKhCzh8IeRoVGzWrRkruMFAJVWPR0yPTECUS/ZJsbrNKMOimkCAjTkBcVqirpuj1GaxOIEd8HCpHY9wElhuTcIUREiYAdaFQW9KFFJU+7TGCg1hqUpNAwXx2Q3eERnmU+PLskvKNNgTpFApIYnyOHyAZffD/hozuwmhKFQBCxnUNWcP3GZTbGa4zX1slZ42OkzY6YPdn3LDuHKTOqUFQqITSoPrFslqQsEcYwMYJzJ84yMBX77oDYr3AuIuKASgxJPiJUSde3LOcFpvS47CiF5ca1fWYLR/ANxkpU3eK6xJotUD6y9DPWpYV9aF2Hqld0ekk4cMTlHkWhySZRZJjHTOsaVl0glxpFwsvnyEzaWKsZvOJe5jc8i60Vrp2hdYEUJc2ipTJDbpuM8eNIbOZUnabzjoQCqaC00IGrFFXSCKGJfQdKMJhWUHQoCwsf2NvbJQvHubMP0c8B75itdlgT51ECmoOOYX1A9ha0J3jDbL7PQAiEirT9LjF4pALVNRhjEJRkMq7rsaphMT9A7RhyahkPNxCmo5ESsiBHTwoBEUs6FTDhOSLSznXP7Xesc2pDc+2Oip1rltUn9yBJYog07ZLWTbB1yZlyiMySA+/okqHWLXWdcFrTtocjtnCZLBTRJgoLdmRpuo7kAv3ujOn4PiZMGJxZYza/wazZwsYVdigQ3rN/kNHFilyuE5Ij+hVLn6mz4mNXfovxiRInYDo5S/QzVrmDHPE5suwa7PIK9GuslwOUMmSraN0OhWvIeUE36qhyRfYBoZ4jj7vtRz5BaUrO3Dbm1LBmdF7xRLiH1aU9SB3OLeg6h1AZgUZbSas1pcqHtpGOaG1RPmBWCZUFSil0IRGiw6XM7n6HEgZlBzjnqTYsOjR4H+jCPhPfIaXGKkGOitneDLlWMt8/oG1aCiNwoiDqjq7PuL4naYNOQEr0JlHWCqJHDywVUwoxRGSFWy6RtSMCSXTo3iOrRCbTiefIIbKoAttP7tDMIifXauppwcQWFKdP0sae4Dt2V3OKrPAaKpfYVJm2LHm6P8DMoBj1KFUQdSTmeChUTDQ20ux1DAuYjC+wOSlIyjM/uErsDf1ihS7Hh1vkfcDUks5FUo7M9+a4JhBEy0QPiF7g+wVJRKIPNN0eUno2qnXs6cBBtYNre9RuSRUTdekQnWI40lwRgl4rVEgsUsCkiIyBcAwG8/HE3Y3HZJsQi4a9xrG7J7FGY4A4KJiOBsxnkdQndKE5aJYMOAymTI1itQAhLZlEZ5fUXpExJCsRGBSOKA16FagnkoPlis7B3C0Y6pJSC1b7C2wpqcl0q4jLnmk1IIqI9AFvNblckNqISgKhS+bza5w8dw/T6ToMGtrBihQdbZxjewW9o6o0OXtI/19755LbRBBF0VOfrv7EbRvHBIiUCGaMWQObZRcMmSMhMUECRUSQOP5316erioG3EAYt+SzhHamk0nu61+EyiB68CQyTQBIDjX/+eM//Iqm6vGJOYh4b7n4+sFWR6aQlaY2zjqaseX1VkbXCPnnqiQQbcQC5wdmMMRKkIwtBV/RcqJIkC1RW1CLg+wOuvme/2oAfeFxHRK5gMiOogbA7MpUG50/r8t465pMZWlqMqdBScSc/n44jRUEhYfnqHW+ub5iamifxB5MUocwUJeioiVi2Q0fYetZWsvMRndfU6sisnSKMZFDPX4PwXyR9vH3LtbrBbzxfHr/xsP7Bui0oY0naBvZCYcyp5EM2Gb2P7EOmywVaSHzugYacwBFOn1OjQEqiszg5gIbHuMH4Hc5FjFnQ6gVGqtOgUqLvI+3Uk2JGFYqUIKYMUWDMFG080pVI6ZE5U1+0XJYLYs7s7UCUEWHAFJGyKem6zDY5bOjph4jzin0WLKtAGjyKgqhHkuPwPtfE44CLDus3RG/pNx1e19RqjttYfnc76rmimbxAvSwx5TXrXyt09vh4IAyn0KaUwKlARaBKBa6Y0JYlNqwIXc9hm6mKBRO15CIZsol0doeSPToPDNGwWR8xFZRa05OZzWq+fv/E8kNGqdMlqpBQ1DV/VweU91h7j751FLVCthW7NhEQdGFH1Af6PpJEpBEClw8cu4gqAxXP/9yd6+JGwLmJbAScJY2As6QRcJY0As6SRsBZ0gj4B0Oi7IUz5fNTAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "visualize_model(model_conv)\n",
    "\n",
    "plt.ioff()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Further Learning\n",
    "-----------------\n",
    "\n",
    "If you would like to learn more about the applications of transfer learning,\n",
    "checkout our `Quantized Transfer Learning for Computer Vision Tutorial <https://pytorch.org/tutorials/intermediate/quantized_transfer_learning.html>`_.\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}
